EDBT 2026 Demo / reviewers in the wild / expert
Alicia Wang
dblp:239/7823
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 77% Usability and user experience research · 23% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › information visualization
personal data visualization |
0.4 | 1 | 2019 | DataSelfie: Empowering People to Design Personalized Visuals to Represent Their Data · CHI 2019 |
Health and well-being technologies
personal informatics |
0.4 | 1 | 2019 | DataSelfie: Empowering People to Design Personalized Visuals to Represent Their Data · CHI 2019 |
Usability and user experience research
usability evaluation |
0.1 | 1 | 2019 | DataSelfie: Empowering People to Design Personalized Visuals to Represent Their Data · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
user study · 0.8design analysis · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | DataSelfie: Empowering People to Design Personalized Visuals to Represent Their DataabstractMany personal informatics systems allow people to collect and manage personal data and reflect more deeply about themselves. However, these tools rarely offer ways to customize how the data is visualized. In this work, we investigate the question of how to enable people to determine the representation of their data. We analyzed the Dear Data project to gain insights into the design elements of personal visualizations. We developed DataSelfie, a novel system that allows individuals to gather personal data and design custom visuals to represent the collected data. We conducted a user study to evaluate the usability of the system as well as its potential for individual and collaborative sensemaking of the data. Hyejin Im, Nathalie Henry Riche, Alicia Wang, Krzysztof Z. Gajos, Hanspeter Pfister |
CHI | 4 |